Graduate Student Researcher

I'm very excited to be spending the Summer of 2019 as a visiting researcher at Invitae, where I'll be working on causal modeling for genetics applications.

__Measuring and Characterizing Generalization in Deep Reinforcement Learning.__ **Sam Witty**, Jun Ki Lee, Emma Tosch, Akanksha Atrey, Michael Littman, David Jensen (2018). arXiv preprint arXiv:1812.02868 (Workshop version published at the NeurIPS Workshop on Critiquing and Correcting Trends in Machine Learning.)

__Causal Graphs vs. Causal Programs: The Case of Conditional Branching.__ **Sam Witty**, David Jensen (2018). Proceedings of the First Conference on Probablistic Programming.

__Belief-Space Planning for Automated Malware Defense.__ Justin Svegliato, **Sam Witty**, Amir Houmansadr, Shlomo Zilberstein (2018). IJCAI Workshop on AI for Internet of Things.

- I presented our
__poster__on "Generalization in Deep Reinforcement Learning" at the__NeurIPS Workshop on Critiquing and Correcting Trends in Machine Learning.__(December 7, 2018) - I presented our
__poster__on "Causal Graphs vs. Causal Models: The Case of Conditional Branching" at the__International Conference on Probabilistic Programming.__(October 5, 2018) - I gave a tutorial on “Causal Inference with Graphical Models” for the
__UMass Graduate Researchers in Data.__(November 29, 2017). - I gave an invited talk on "Computational Representations of Causality" for the
__MIT Probabilistic Computing Group.__(November 2, 2017)

- I'm the teaching assistant for
__CS348__, Umass' upper-level undergraduate course on data science. (Spring, 2019) - I gave a guest lecture on deep learning for CS589, Umass' Masters course on machine learning. (February 15, 2018)
- I mentored Catherine Chen, a visiting undergraduate researcher sponsored by the NSF's REU program. (Summer, 2017)